Emotion Recognition from Hindi Speech using MFCC and Sparse DTW

Emotion Recognition from Hindi Speech using MFCC and Sparse DTW
Authors : Er. Vipinkumar R. Pawar, Ms. Nupur Patel
Publication Date: 01-06-2015


Author(s):  Er. Vipinkumar R. Pawar, Ms. Nupur Patel

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Volume. 4 - Issue. 06 , June - 2015

e-ISSN:   2278-0181

 DOI:  http://dx.doi.org/10.17577/IJERTV4IS060003


Recently increasing attention has been directed to the study of emotional content of speech signals, and hence, many systems have been proposed to identify the emotional content of a spoken utterance. The project of Emotion Recognition from Hindi Speech address to three main aspects of speech recognition system. The first one is the choice of suitable features for speech representation. Using Sparse DTW for feature recognition has improved space efficiency and time complexity. Implementation of automatic emotion recognition system (using MATLAB) provides an accuracy of over 75% for 5 emotions namely: happy, sad, surprise, anger and neutral over a database containing large variety of speakers.


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